transformers - 💡(How to fix) Fix table-question-answering task crashes

transformers2026-05-11 21:33:49

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Error Message

(.venv) C:\Users\usuario\Documents\aibased>transformers env Traceback (most recent call last): File "<frozen runpy>", line 198, in _run_module_as_main File "<frozen runpy>", line 88, in run_code File "C:\Users\usuario\Documents\aibased.venv\Scripts\transformers.exe_main.py", line 4, in <module> from transformers.cli.transformers import main File "C:\Users\usuario\Documents\aibased.venv\Lib\site-packages\transformers\cli\transformers.py", line 19, in <module> from transformers.cli.chat import Chat File "C:\Users\usuario\Documents\aibased.venv\Lib\site-packages\transformers\cli\chat.py", line 26, in <module> import requests ModuleNotFoundError: No module named 'requests'

(.venv) C:\Users\usuario\Documents\aibased>

Code Example

(.venv) C:\Users\usuario\Documents\aibased>transformers env
Traceback (most recent call last):
  File "<frozen runpy>", line 198, in _run_module_as_main
  File "<frozen runpy>", line 88, in _run_code
  File "C:\Users\usuario\Documents\aibased\.venv\Scripts\transformers.exe\__main__.py", line 4, in <module>
    from transformers.cli.transformers import main
  File "C:\Users\usuario\Documents\aibased\.venv\Lib\site-packages\transformers\cli\transformers.py", line 19, in <module>
    from transformers.cli.chat import Chat
  File "C:\Users\usuario\Documents\aibased\.venv\Lib\site-packages\transformers\cli\chat.py", line 26, in <module>
    import requests
ModuleNotFoundError: No module named 'requests'

(.venv) C:\Users\usuario\Documents\aibased>

---

(.venv) C:\Users\usuario\Documents\aibased>C:/Users/usuario/AppData/Local/Programs/Python/Python313/python.exe -m pip list                               
Package            Version
------------------ -----------
aiohappyeyeballs   2.6.1
aiohttp            3.13.5
aiosignal          1.4.0
annotated-doc      0.0.4
anyio              4.13.0
attrs              26.1.0
certifi            2026.4.22
charset-normalizer 3.4.7
click              8.3.3
colorama           0.4.6
datasets           4.8.5
dill               0.4.1
filelock           3.29.0
frozenlist         1.8.0
fsspec             2026.2.0
h11                0.16.0
hf-xet             1.5.0
httpcore           1.0.9
httpx              0.28.1
huggingface_hub    1.14.0
idna               3.14
Jinja2             3.1.6
markdown-it-py     4.2.0
MarkupSafe         3.0.3
mdurl              0.1.2
mpmath             1.3.0
multidict          6.7.1
multiprocess       0.70.19
networkx           3.6.1
numpy              2.4.4
packaging          26.2
pandas             3.0.3
pip                25.1.1
propcache          0.5.2
pyarrow            24.0.0
Pygments           2.20.0
python-dateutil    2.9.0.post0
PyYAML             6.0.3
regex              2026.5.9
requests           2.33.1
rich               15.0.0
safetensors        0.7.0
setuptools         81.0.0
shellingham        1.5.4
six                1.17.0
sympy              1.14.0
tokenizers         0.22.2
torch              2.11.0
torch_scatter      2.1.2
tqdm               4.67.3
transformers       5.8.0
typer              0.25.1
typing_extensions  4.15.0
tzdata             2026.2
urllib3            2.7.0
xxhash             3.7.0
yarl               1.23.0

(.venv) C:\Users\usuario\Documents\aibased>

---

from transformers import pipeline
import pandas as pd

# prepare table + question
data = {"Actors": ["Brad Pitt", "Leonardo Di Caprio", "George Clooney"], "Number of movies": ["87", "53", "69"]}
table = pd.DataFrame.from_dict(data)
question = "how many movies does Leonardo Di Caprio have?"

# pipeline model
# Note: you must to install torch-scatter first.
tqa = pipeline(task="table-question-answering", model="google/tapas-large-finetuned-wtq")

# result

print(tqa(table=table, query=question)['cells'][0])
#53

---

Loading weights: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████| 403/403 [00:00<00:00, 14159.26it/s]
Traceback (most recent call last):
  File "c:\Users\usuario\Documents\aibased\main.py", line 15, in <module>
    print(tqa(table=table, query=question)['cells'][0])
          ~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\pipelines\table_question_answering.py", line 285, in __call__
    results = super().__call__(pipeline_inputs, **kwargs)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\pipelines\base.py", line 1247, in __call__
    outputs = list(final_iterator)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\pipelines\pt_utils.py", line 126, in __next__
    item = next(self.iterator)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\pipelines\pt_utils.py", line 126, in __next__
    item = next(self.iterator)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\torch\utils\data\dataloader.py", line 741, in __next__
    data = self._next_data()
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\torch\utils\data\dataloader.py", line 801, in _next_data
    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\torch\utils\data\_utils\fetch.py", line 54, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
            ~~~~~~~~~~~~^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\pipelines\pt_utils.py", line 19, in __getitem__
    processed = self.process(item, **self.params)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\pipelines\table_question_answering.py", line 321, in preprocess
    inputs = self.tokenizer(table, query, return_tensors="pt", truncation=truncation, padding=padding)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\models\tapas\tokenization_tapas.py", line 619, in __call__
    return self.encode_plus(
           ~~~~~~~~~~~~~~~~^
        table=table,
        ^^^^^^^^^^^^
    ...<17 lines>...
        **kwargs,
        ^^^^^^^^^
    )
    ^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\models\tapas\tokenization_tapas.py", line 982, in encode_plus
    return self._encode_plus(
           ~~~~~~~~~~~~~~~~~^
        table=table,
        ^^^^^^^^^^^^
    ...<16 lines>...
        **kwargs,
        ^^^^^^^^^
    )
    ^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\models\tapas\tokenization_tapas.py", line 1034, in _encode_plus
    return self.prepare_for_model(
           ~~~~~~~~~~~~~~~~~~~~~~^
        table,
        ^^^^^^
    ...<17 lines>...
        verbose=verbose,
        ^^^^^^^^^^^^^^^^
    )
    ^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\models\tapas\tokenization_tapas.py", line 1170, in prepare_for_model
    raw_table = add_numeric_table_values(raw_table)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\models\tapas\tokenization_tapas.py", line 2770, in add_numeric_table_values
    table.iloc[row_index, col_index] = Cell(text=cell)
    ~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\indexing.py", line 938, in __setitem__
    iloc._setitem_with_indexer(indexer, value, self.name)
    ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\indexing.py", line 1953, in _setitem_with_indexer
    self._setitem_with_indexer_split_path(indexer, value, name)
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\indexing.py", line 2044, in _setitem_with_indexer_split_path
    self._setitem_single_column(loc, value, pi)
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\indexing.py", line 2181, in _setitem_single_column
    self.obj._mgr.column_setitem(loc, plane_indexer, value)
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\internals\managers.py", line 1528, in column_setitem
    new_mgr = col_mgr.setitem((idx,), value)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\internals\managers.py", line 607, in setitem
    return self.apply("setitem", indexer=indexer, value=value)
           ~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\internals\managers.py", line 445, in apply
    applied = getattr(b, f)(**kwargs)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\internals\blocks.py", line 1667, in setitem
    values[indexer] = value
    ~~~~~~^^^^^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\arrays\arrow\array.py", line 2237, in __setitem__
    value = self._maybe_convert_setitem_value(value)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\arrays\string_arrow.py", line 298, in _maybe_convert_setitem_value
    if len(value) and not (
       ~~~^^^^^^^
TypeError: len() of unsized object

RAW_BUFFERClick to expand / collapse

System Info

(.venv) C:\Users\usuario\Documents\aibased>transformers env
Traceback (most recent call last):
  File "<frozen runpy>", line 198, in _run_module_as_main
  File "<frozen runpy>", line 88, in _run_code
  File "C:\Users\usuario\Documents\aibased\.venv\Scripts\transformers.exe\__main__.py", line 4, in <module>
    from transformers.cli.transformers import main
  File "C:\Users\usuario\Documents\aibased\.venv\Lib\site-packages\transformers\cli\transformers.py", line 19, in <module>
    from transformers.cli.chat import Chat
  File "C:\Users\usuario\Documents\aibased\.venv\Lib\site-packages\transformers\cli\chat.py", line 26, in <module>
    import requests
ModuleNotFoundError: No module named 'requests'

(.venv) C:\Users\usuario\Documents\aibased>

Adding extra info about package versions:

(.venv) C:\Users\usuario\Documents\aibased>C:/Users/usuario/AppData/Local/Programs/Python/Python313/python.exe -m pip list                               
Package            Version
------------------ -----------
aiohappyeyeballs   2.6.1
aiohttp            3.13.5
aiosignal          1.4.0
annotated-doc      0.0.4
anyio              4.13.0
attrs              26.1.0
certifi            2026.4.22
charset-normalizer 3.4.7
click              8.3.3
colorama           0.4.6
datasets           4.8.5
dill               0.4.1
filelock           3.29.0
frozenlist         1.8.0
fsspec             2026.2.0
h11                0.16.0
hf-xet             1.5.0
httpcore           1.0.9
httpx              0.28.1
huggingface_hub    1.14.0
idna               3.14
Jinja2             3.1.6
markdown-it-py     4.2.0
MarkupSafe         3.0.3
mdurl              0.1.2
mpmath             1.3.0
multidict          6.7.1
multiprocess       0.70.19
networkx           3.6.1
numpy              2.4.4
packaging          26.2
pandas             3.0.3
pip                25.1.1
propcache          0.5.2
pyarrow            24.0.0
Pygments           2.20.0
python-dateutil    2.9.0.post0
PyYAML             6.0.3
regex              2026.5.9
requests           2.33.1
rich               15.0.0
safetensors        0.7.0
setuptools         81.0.0
shellingham        1.5.4
six                1.17.0
sympy              1.14.0
tokenizers         0.22.2
torch              2.11.0
torch_scatter      2.1.2
tqdm               4.67.3
transformers       5.8.0
typer              0.25.1
typing_extensions  4.15.0
tzdata             2026.2
urllib3            2.7.0
xxhash             3.7.0
yarl               1.23.0

(.venv) C:\Users\usuario\Documents\aibased>

Who can help?

@Rocketknight1

Information

The official example scripts
My own modified scripts

Tasks

An officially supported task in the examples folder (such as GLUE/SQuAD, ...)
My own task or dataset (give details below)

Reproduction

Copy script from: https://huggingface.co/tasks/table-question-answering

Which is:

from transformers import pipeline
import pandas as pd

# prepare table + question
data = {"Actors": ["Brad Pitt", "Leonardo Di Caprio", "George Clooney"], "Number of movies": ["87", "53", "69"]}
table = pd.DataFrame.from_dict(data)
question = "how many movies does Leonardo Di Caprio have?"

# pipeline model
# Note: you must to install torch-scatter first.
tqa = pipeline(task="table-question-answering", model="google/tapas-large-finetuned-wtq")

# result

print(tqa(table=table, query=question)['cells'][0])
#53

At end it throws an exception in pandas, giving stacktrace:

Loading weights: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████| 403/403 [00:00<00:00, 14159.26it/s]
Traceback (most recent call last):
  File "c:\Users\usuario\Documents\aibased\main.py", line 15, in <module>
    print(tqa(table=table, query=question)['cells'][0])
          ~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\pipelines\table_question_answering.py", line 285, in __call__
    results = super().__call__(pipeline_inputs, **kwargs)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\pipelines\base.py", line 1247, in __call__
    outputs = list(final_iterator)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\pipelines\pt_utils.py", line 126, in __next__
    item = next(self.iterator)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\pipelines\pt_utils.py", line 126, in __next__
    item = next(self.iterator)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\torch\utils\data\dataloader.py", line 741, in __next__
    data = self._next_data()
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\torch\utils\data\dataloader.py", line 801, in _next_data
    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\torch\utils\data\_utils\fetch.py", line 54, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
            ~~~~~~~~~~~~^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\pipelines\pt_utils.py", line 19, in __getitem__
    processed = self.process(item, **self.params)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\pipelines\table_question_answering.py", line 321, in preprocess
    inputs = self.tokenizer(table, query, return_tensors="pt", truncation=truncation, padding=padding)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\models\tapas\tokenization_tapas.py", line 619, in __call__
    return self.encode_plus(
           ~~~~~~~~~~~~~~~~^
        table=table,
        ^^^^^^^^^^^^
    ...<17 lines>...
        **kwargs,
        ^^^^^^^^^
    )
    ^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\models\tapas\tokenization_tapas.py", line 982, in encode_plus
    return self._encode_plus(
           ~~~~~~~~~~~~~~~~~^
        table=table,
        ^^^^^^^^^^^^
    ...<16 lines>...
        **kwargs,
        ^^^^^^^^^
    )
    ^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\models\tapas\tokenization_tapas.py", line 1034, in _encode_plus
    return self.prepare_for_model(
           ~~~~~~~~~~~~~~~~~~~~~~^
        table,
        ^^^^^^
    ...<17 lines>...
        verbose=verbose,
        ^^^^^^^^^^^^^^^^
    )
    ^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\models\tapas\tokenization_tapas.py", line 1170, in prepare_for_model
    raw_table = add_numeric_table_values(raw_table)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\transformers\models\tapas\tokenization_tapas.py", line 2770, in add_numeric_table_values
    table.iloc[row_index, col_index] = Cell(text=cell)
    ~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\indexing.py", line 938, in __setitem__
    iloc._setitem_with_indexer(indexer, value, self.name)
    ~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\indexing.py", line 1953, in _setitem_with_indexer
    self._setitem_with_indexer_split_path(indexer, value, name)
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\indexing.py", line 2044, in _setitem_with_indexer_split_path
    self._setitem_single_column(loc, value, pi)
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\indexing.py", line 2181, in _setitem_single_column
    self.obj._mgr.column_setitem(loc, plane_indexer, value)
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\internals\managers.py", line 1528, in column_setitem
    new_mgr = col_mgr.setitem((idx,), value)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\internals\managers.py", line 607, in setitem
    return self.apply("setitem", indexer=indexer, value=value)
           ~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\internals\managers.py", line 445, in apply
    applied = getattr(b, f)(**kwargs)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\internals\blocks.py", line 1667, in setitem
    values[indexer] = value
    ~~~~~~^^^^^^^^^
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\arrays\arrow\array.py", line 2237, in __setitem__
    value = self._maybe_convert_setitem_value(value)
  File "C:\Users\usuario\AppData\Local\Programs\Python\Python313\Lib\site-packages\pandas\core\arrays\string_arrow.py", line 298, in _maybe_convert_setitem_value
    if len(value) and not (
       ~~~^^^^^^^
TypeError: len() of unsized object

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